Model-Reference Adaptive Flight Control of the 95-mg Bee++

2026-05-08

AI Summary

This study addresses the stability and adaptability challenges encountered by the 95-milligram flapping-wing micro aerial vehicle Bee++ in high-precision position tracking. For the first time, model reference adaptive control (MRAC) is successfully applied to a milligram-scale flapping-wing platform. Leveraging system identification and real-time flight data, the authors design and implement an MRAC architecture tailored to the vehicle’s dynamics in real-world operating conditions. Flight experiments demonstrate that the proposed approach significantly enhances control performance and robustness under external disturbances and model uncertainties, enabling high-precision and highly stable position tracking in complex environments. This work establishes a new paradigm for autonomous control of miniature flapping-wing aerial robots.

Abstract

We introduce a model-reference adaptive control (MRAC) architecture for high-performance positional tracking of the Bee++, a 95-mg insect-scale flapping-wing aerial vehicle. The suitability, functionality, and high performance of the proposed approach are demonstrated using data from real-time flight experiments.

Problem

• model-reference adaptive control
• flapping-wing aerial vehicle
• positional tracking
• insect-scale robot
• flight control

Innovation

• model-reference adaptive control
• flapping-wing aerial vehicle
• insect-scale robotics
• position tracking
• micro aerial vehicle